Triangle

Course overview

Insights from data science are most valuable when they exist alongside a knowledge and understanding of the ways in which individuals, businesses and governments make decisions.

On our Economics and Data Science MSc, you will learn about the data science methods used widely in economic analysis, such as Lasso, random forests and supervised learning.

You will take specialist core modules that will teach key methods such as machine learning and coding, economic decision making and their application in economics. You can choose from a range of options to suit your interests and career goals. You will also undertake a dissertation in big data economics.

With an advanced degree in economics and data science from the University of Nottingham, you will graduate with all the knowledge, practical skills and confidence you need to stand out to employers and progress as a professional economist, policy maker or academic researcher.

Why choose this course?

Flexible course

with a range of modules informed by our world-leading research

Modern techniques

Learn modern techniques in Machine Learning and Big Data

One-to-one supervision

by a faculty member for your dissertation

Gain real experience

by applying for internships and placements through our faculty placements scheme

Top 100

in the world for economics

Course content

This course comprises 120 credits of core and optional taught modules, plus a 60-credit dissertation on a subject of your choice.

Semester one

In semester one, you will take the core module, Machine Learning for Economics, along with modules in microeconomics or macroeconomics, econometric theory and economic data analysis.

Semester two

In semester two, you will take the advanced core module, Big Data Economics, and choose three optional modules. You will also start work on your dissertation by taking a module in economic research methodology.

Dissertation

After completing your semester two modules, you will undertake a 15,000-word supervised dissertation, with one-to-one support from an expert academic supervisor. This will apply the machine learning and big data techniques to an economic research question.

Modules

Core modules

Microeconomic Theory

This module covers:

  • modern techniques of microeconomic theory
  • foundations and applications of game theory
  • information economics
Macroeconomic Theory

This module will cover analytical and theoretical issues in macroeconomics including:

  • modelling aggregate variables under adaptive and rational expectations
  • modelling with imperfect competition
  • constructing overlapping generations models
  • price inertia
Econometric Theory

This module teaches the core techniques of econometric theory, including:

  • detailed analysis of the multiple linear regression model
  • large sample theory
  • asymptotic testing procedures
  • non-linear techniques
  • mis-specification testing
Economic Data Analysis

This module provides you with 'hands on' training in the use, presentation and interpretation of economic data, including time series, cross-section and panel data. It comprises of:

  • an introduction to basic principles of economic data analysis
  • descriptive statistics
  • hypothesis testing
  • simple and multiple regression
  • introduction to panel data
  • introduction to dynamic modelling
  • time series models

The module will include a series of practical classes using econometrics software packages.

Machine Learning for Economics

This module is intended as an introduction of the methodology and implementation of machine learning methods used widely in economic analysis; the module provides an introduction to the analysis of large datasets, with more up to date Big Data methods introduced later as natural developments. Topics will include:

  • an introduction to statistical computing in R
  • generating random variables and random processes
  • Monte Carlo integration and variance reduction; high performance computing
  • multivariate linear regression
  • classification
  • resampling methods
  • linear model selection and regularization
Big Data Economics

This module will focus on advanced Big Data methods and their applications in various economics problems. Topics of the module include:

  • nonlinear models
  • tree-based models
  • support vector machines
  • unsupervised learning and applications in international trade
  • household finance
  • macro forecasting
  • labor economics
  • text analysis
Economic Research Methodology

This module covers the following:

  • A review of perspectives on the principles and philosophical foundations of economic enquiry
  • The construction and evaluation of theories and research programmes
  • The role of models and concepts of rationality in economics
  • Alternative empirical methods
  • Professional practice

Optional modules

Three from:

Advanced Macroeconomic Methods

This module covers the theory for the solution and estimation of dynamic stochastic models that are widely used in all fields of macroeconomics. The module is structured in a way such that you will be exposed both to theory and the practical implementation of the methods taught.

It covers topics from approximation methods for stochastic non-linear macroeconomic models, such as linear and higher-order Taylor approximation as well as dynamic programming techniques. It also exposes students to the empirical evaluation of these models ranging from calibration to classical and Bayesian estimation methods.

The module applies the techniques to contemporary general equilibrium macroeconomic models designed for positive and policy analysis such as the New Keynesian model but also models that are designed to explain partial equilibrium behaviour such as consumer saving and industry investment.

International Macroeconomics

This module covers the following:

  • International linkages in economics as a result of exchange rate movements, capital movements and spillovers
  • Factors which determine the level of the exchange rate and trade effects
  • International effects of monetary and fiscal policies
Monetary Theory and Practice

This module covers monetary aspects of advanced macroeconomics and is suitable for students of mainstream economics, finance and international economics. It focuses on the theory and practice of central banking, monetary policy and control.

It covers concepts such as time inconsistency, the problem of inflation bias with solutions, credibility, transparency and accountability of monetary institutions, inflation targeting and price stability, the choice of instruments for monetary policy and their control, and finally monetary transmission. It combines some theory with evidence and practice.

Time Series Econometrics

The module covers fundamental properties of time series and various classes of stochastic processes. Issues in estimation and forecasting of time series models; concepts of contemporary interest to time series econometricians are also covered.

Financial and Macroeconometrics

The module extends the coverage of advanced econometric modelling techniques and considers their application through the study of selected topics in finance and macroeconomics, developing familiarity and critical awareness of empirical research in these areas.

It covers techniques for the analysis of stationary ARMA processes, Vector Autoregressions (VARs), linear regression models, linear systems of simultaneous equations, cointegration, long-run structural VARs, forecasting, and models of changing volatility. The selected topics include the econometric analysis of business cycle fluctuations, wage, price and (un)employment determination, portfolio choice and stock market returns.

Applied Microeconometrics

The module considers modern econometric techniques for modelling microeconomic data. It covers four broad econometric techniques:

  • Robust standard errors and applications
  • Discrete choices model
  • Microeconometric policy evaluation methods for observational studies
  • Instrumental variables and GMM estimation
Economics of Corporate Finance

This module offers an introduction to the economics of corporate finance. It is designed to provide you with the basic theoretical background in this area that is necessary for any applied work. Emphasis is placed on the analysis of simple models and their applications.

The module covers a variety of topics with substantial time devoted for covering issues directly related to the financial needs of firms, such as capital structure, credit rationing and corporate governance.

The module also examines the role of financial intermediaries analysing bank failures and, consequently, the scope for banking regulations. The last part of the module looks closely at the relationship between the financial sector and the real economy thus offering the background for any applied work related to the link between financial development and economic fluctuations.

Economics of Household Finance

This module covers the central issues in the economics of household finance. Increasingly economists are interested in the decisions of consumers as well as the decisions of firms.

Household finance is the study of the behaviour of individuals and households in financial markets including those for secured (for example, mortgage) and unsecured (for example, credit card) lending and related economic models of consumption smoothing, liquidity constraints and household behaviour.

The module begins with the central topic of consumption smoothing, focusing on the role of credit markets and income risk in household behaviour. Later topics include financial literacy, self-control, mortgage market design, stock market participation and the regulation of consumer credit markets.

The module content includes come theoretical material but is mostly applied, with a focus on how large-scale individual level proprietary and survey datasets can be used to understand household financial behaviour.

Additional electives from existing MSc semester two modules will also be available (eg in Behavioural Economics, Public Economics, International Economics).

The above is a sample of the typical modules we offer but is not intended to be construed and/or relied upon as a definitive list of the modules that will be available in any given year. Modules (including methods of assessment) may change or be updated, or modules may be cancelled, over the duration of the course due to a number of reasons such as curriculum developments or staffing changes. Please refer to the module catalogue for information on available modules. This content was last updated on Wednesday 13 October 2021.

Learning and assessment

How you will learn

  • Lectures
  • Seminars
  • Tutorials
  • Workshops

How you will be assessed

  • Coursework
  • Project work
  • Presentation
  • Dissertation

Modules are assessed by a combination of exams and coursework at the end of the relevant semester.

Contact time and study hours

Each module in semester one will have three contact hours per week, made up of a mixture of lectures, tutorials and lab classes. For each contact hour, we expect you to spend an additional three hours of self-study, reading, completing homework, assignments and studying for exams.

Each module in semester two will have two contact hours per week, and we expect you to spend slightly more time in self-study as you start to work on your dissertation. During June, July and August, you will work on your dissertation, supported by a minimum of three one-to-one supervision meetings with your supervisor.

Entry requirements

All candidates are considered on an individual basis and we accept a broad range of qualifications. The entrance requirements below apply to 2022 entry.

Undergraduate degree2:1 (or international equivalent) in a discipline with significant economics content, including some mathematical and quantitative methods modules

Applying

Our step-by-step guide covers everything you need to know about applying.

How to apply

Fees

All listed fees are per year of study.

Qualification MSc
Home / UK £13,700
International £23,500

Additional information for international students

If you are a student from the EU, EEA or Switzerland, you will pay international tuition fees in most cases. If you are resident in the UK and have 'settled' or 'pre-settled' status under the EU Settlement Scheme, you will be entitled to 'home' fee status.

Irish students will be charged tuition fees at the same rate as UK students. UK nationals living in the EU, EEA and Switzerland will also continue to be eligible for ‘home’ fee status at UK universities until 31 December 2027.

For further guidance, check our information for applicants from the EU.

These fees are for full-time study. If you are studying part-time, you will be charged a proportion of this fee each year (subject to inflation).

Additional costs

As a student on this course, you should factor some additional costs into your budget, alongside your tuition fees and living expenses.

You should be able to access most of the books you’ll need through our libraries, though you may wish to purchase your own copies or more specific titles which could cost up to £50-60.

Please note that these figures are approximate and subject to change.

Funding

There are many ways to fund your postgraduate course, from scholarships to government loans.

We also offer a range of international masters scholarships for high-achieving international scholars who can put their Nottingham degree to great use in their careers.

Check our guide to find out more about funding your postgraduate degree.

Postgraduate funding

Careers

We offer individual careers support for all postgraduate students.

Expert staff can help you research career options and job vacancies, build your CV or résumé, develop your interview skills and meet employers.

Each year 1,100 employers advertise graduate jobs and internships through our online vacancy service. We host regular careers fairs, including specialist fairs for different sectors.

International students who complete an eligible degree programme in the UK on a student visa can apply to stay and work in the UK after their course under the Graduate immigration route. Eligible courses at the University of Nottingham include bachelors, masters and research degrees, and PGCE courses.

Graduate destinations

Our economics masters provides a logical and rigorous perspective on human behaviour which is valued by a wide range of employers around the world, in banking, business, consulting, government and academia.

Our graduates now work in academia, government and the private sector, at organisations such as Barclays, Bloomberg, Deloitte, Economist Intelligence Unit, Goldman Sachs, IBM, PwC, and Thomson Reuters.

Career progression

93.8% of postgraduates from the School of Economics secured graduate level employment or further study within 15 months of graduation. The average annual salary for these graduates was £31,605.*

* HESA Graduate Outcomes 2020, using methodology set by The Guardian. The average annual salary is based on graduates working full-time within the UK.

This course does not include an integrated placement option. However, you will have the opportunity to apply for internships and placements through the Postgraduate Placements Nottingham (PPN) scheme and the Faculty of Social Sciences placements scheme.

Two masters graduates proudly holding their certificates

Related courses

This content was last updated on Wednesday 13 October 2021. Every effort has been made to ensure that this information is accurate, but changes are likely to occur given the interval between the date of publishing and course start date. It is therefore very important to check this website for any updates before you apply.